In a the wireless communication technology, when a first-class node, such as an eNode B, eNB, sends data by using multiple antennae, a spatial multiplexing mode may be used to improve a the data transmission rate may be improved by using a spatial multiplexing mode. That is, the first-class node transmits different data at different antenna positions by using the same time-frequency resources. A second-class node, such as User Equipment UE, also receives data by using multiple antennae. Resources of all the antennae are allocated to one user in a single-user situation, and the user monopolizes physical resources allocated by the eNB side in a transmission interval, and the transmission mode is called Single User Multiple-Input Multiple-Output SU-MIMO. Space resources of different antennae are allocated to different users in a multi-user situation, and one user and at least one of other users share the physical resources allocated by the eNB side in a transmission interval. Herein, a sharing mode may be a Spatial Division Multiple Access mode or Spatial Division Multiplexing mode, and the transmission mode is called Multiple User Multiple-Input Multiple-Output MU-MIMO. Herein, the physical resources allocated by the eNB side are time-frequency resources, as shown in FIG. 1.
In a Long Term Evolution LTE system, Channel State Information CSI reflecting a downlink physical channel state has three forms: a Channels Quality Indication CQI, a Pre-coding Matrix Indicator PMI) and a Rank Indicator RI.
The CQI is an index for measuring the quality of the downlink channel. In the related art, the CQI is expressed by using integral values 0-15, which represent different CQI grades respectively. Different CQIs correspond to respective Modulation and Coding Schemes MCS, which is divided into 16 situations and may be expressed by using 4 bit information.
The PMI refers to that the eNB is informed to use what type of pre-coding matrix for pre-coding of a Physical Downlink Shared Channel, PDSCH, of the UE according to the measured quality of channel only in a transmission mode namely closed-loop spatial multiplexing. The feedback granularity of the PMI may be the feedback granularity of one PMI based on an entire bandwidth, or may be the feedback granularity of one PMI based on a subband.
The RI is used for describing the number of spatial independent channels, and corresponds to rank of channel responding matrix. Under an open-loop spatial multiplexing mode and a closed-loop spatial multiplexing mode, the UE needs to feed back RI information, and under other modes, the UE does not need to feed back the RI information. A rank of a channel matrix corresponds to the number of layers, and therefore feeding back, by the UE, the RI information to the eNB refers to feeding back the number of downlink transmission layers.
A transmission layer is a concept of multi-antenna “layer” in the LTE and an LTE-A, and represents the number of effective valid independent channels in spatial multiplexing. The total number of transmission layers is a rank of spatial channels. Under the SU-MIMO mode, resources of all antennae are allocated to one user, and the number of layers used for transmitting MIMO data is equal to a rank used by the eNB for transmitting the MIMO data. Under the MU-MIMO mode, the number of layers used for transmission in correspondence to of one user is smaller than the total number of layers used by the eNB for transmitting the MIMO data. If the SU-MIMO mode and the MU-MIMO mode need to be switched, the eNB needs to inform the UE of different control data under different transmission modes.
Device-to-Device D2D communication is a technology for direct communication between terminals. The main features are that: a certain device in multiple devices under network coverage and within a short distance may find other devices in a wireless manner, and direct connection and communication between the devices can be realized. The D2D communication shares resources with cell users under the control of a cell network, and therefore the utilization rate of spectrum will be improved. In addition, the D2D communication can also bring the advantages including: alleviating burdens on a cellular network, reducing the power consumption of a battery of a mobile terminal, improving a bit rate, improving the fault robustness of a network infrastructure and the like, and further supporting novel small-scale point-to-point data service.
In an actual communication system, the first-class node, such as the eNB side, may adopt multiple transmitting and receiving antennae. Due to limitation of factors such as volume and cost and the like, the second-class node, such as the user side, will not be configured with too many antennae usually, so the advantages of the MIMO technology cannot be fully played.
According to an uplink virtual MIMO method proposed at present, multiple second-class nodes are combined to form a virtual MIMO channel in the same time-frequency resource, and send data to an eNB having multiple antennae in a combination way. When the distance between the second-class nodes is large enough, channels where different second-class nodes reach the first-class node may be regarded to be unrelated. Therefore, the factors such as volume and cost are overcome.
The virtual MIMO is divided into two types, i.e., collaborative virtual MIMO and non-collaborative virtual MIMO. The collaborative virtual MIMO refers to that data between the second-class nodes may be shared. A virtual multi-antenna system is formed by sharing respective antennae. An uplink collaborative virtual MIMO technology in the related art mainly implements an MIMO diversity function. The non-collaborative virtual MIMO refers to that data between the second-class nodes cannot be shared, and independent data streams are sent to the first-class node respectively instead. In the non-collaborative virtual MIMO, the first-class node selects several second-class nodes for pairing according to channel situation of the second-class nodes, and the paired second-class nodes send data to the eNB on the same time-frequency resource, and the first-class node distinguishes different second-class nodes by means of multiple antennae, which is similar to downlink MU-MIMO to some extent. The non-collaborative virtual MIMO mainly implements an MIMO multiplexing function.
The virtual MIMO technology is usually suggested to be applied to an uplink where the second-class nodes send data to the first-class node, and the virtual MIMO technology adopts a non-collaborative mode usually.
As shown in FIG. 2, the downlink virtual MIMO may share receiving antennae of multiple second-class nodes to form a virtual second-class node. The virtual second-class node is similar to an SU-MIMO receiver. Due to low interlayer interference, compared to the MU-MIMO as which the multiple second-class nodes are used, the virtual second-class node can obtain a better link performance and a larger downlink throughput, which is greatly advantageous in improvement of a communication situation of a hotspot region where second-class nodes are relatively dense. However, the downlink virtual MIMO is collaborative virtual MIMO essentially, and the second-class nodes need to share information received from the first-class node and perform combined demodulation and decoding. The data sharing is performed by means of a D2D wireless link and other wireless links usually. Thus, the second-class nodes for performing virtual MIMO are certainly limited to some extent, for example, the second-class nodes are relatively close to each other in geographical location, and they are in one cluster usually. The cluster here refers to a set of the second-class nodes relatively close to each other in geographical location. One of the set of the second-class nodes may share channel information and/or received data with one of other second-class nodes at least. If the activation number of second-class nodes in a cluster is small or channels therebetween are relatively related, even if they were performed the virtual MIMO pairing to form a virtual node, the performance improvement is not obvious probably. Since the MU-MIMO does not need data interaction between the second-class nodes, second-class nodes may be selected from different clusters for pairing to form the MU-MIMO. The performance of the MU-MIMO is probably better than the performance of the virtual MIMO in which pairing is performed in the same cluster.
In addition, as shown in FIG. 3, when there are few first-class node antennae, to pair, sometimes, other second-class nodes to improve the performance, it is necessary to limit the number of receiving antenna ports of a second-class node having more receiving antennae. That is, some receiving antenna ports of the second-class node constitute a virtual MIMO to transmit and receive data. Here, an MIMO mode in such a form is also called virtual MIMO, and the second-class node is called virtual port node.
However, current transmission solutions do not include a data transmission solution for forming MU-MIMO by pairing between virtual second-class nodes and second-class nodes of other clusters or virtual second-class nodes, and also do not include a data transmission solution for forming the MU-MIMO by means of some second-class nodes in one cluster.